A Lesson In Clinical Decision Support: We Cannot Defeat Human Nature

      Our UCSF Clinical Informatics group met a few months ago with several representatives from a major Health IT vendor. The vendor, we’ll call them RxLabs, is a provider of pharmaceutical related knowledge in many domains, including decision support tools for the EHR. Our conversation centered around how to better customize medication alerts. We talked about the popular topic of “alert fatigue,” and how to improve EHR decision support tools to improve their impact, rather than just being white noise annoying clinicians.
      The vendor was walking us through a slide-deck about their hypotheses and data about EHR medication alerts and we were having a vibrant discussion about how to improve provider adherence with decision support. We saw slide after slide about how to make pop-ups smarter and about trying to get more buy-in from providers with paying attention to alerts. After all, why would a provider trying to take care of her patient ignore an alert that is trying to help provide an important message? It must be sloppiness or laziness on the part of providers!
      Ten minutes in to this conversation about drug alerts, up pops the following:
Windows 7 Display Alert
      I’ll give you a second to guess what happened next.
      Without a moment’s hesitation or thought, the presenter clicked the little X in the upper right corner. Our conversation went on. More slides. More data about medication alerts in the EHR. Ten minutes later, guess what happened?
      Up came the same pop-up Windows alert. The presenter again, hastily, without paying attention, and perhaps giving a small huff of displeasure, clicked the little X in the upper right corner. More slides, ten more minutes, same thing. You get the idea.
      This happened three times, with each passing pop-up, the presenter becoming slightly more annoyed. The fourth time the pop-up appeared, my colleague Russ Cucina, the Associate CMIO at UCSF, paused the presenter to have us all read the pop-up alert message. We took ten seconds together to learn that selecting any of the three choices rather than clicking the “x” would have satisfied the alert and kept it from coming back.
      The room broke out into laughter. We all understood our own hypocrisy. We cannot defeat human nature.

Feedback Loops and Teachable Moments: The Future Diabetes Care Paradigm

The current paradigm of office visits every three months for PWDs (people with diabetes) is not the right model (nor is it for other similar chronic conditions).  The management of diabetes requires a patient to make dozens of daily self-management decisions.  “How much insulin should I give for this slice of pizza?  Do I need to eat a snack to prevent my blood sugar from going low before I go for a jog?”  Diabetes related questions and issues do not occur on an every-three month basis in synch with this current model for office visits.  They are predictably unpredictable.  Accordingly, to best serve our patients, our system must be flexible and nimble.

In the current model, I see a PWD in my office and let’s say, for example, that we decide together to make a change to his insulin to carbohydrate dosing ratio.  He then leaves my office and we wait three months to reconvene and see if that dosing plan change is working or not.  It’s not that it takes three months to decide.  We could probably know within a week or two if the change is working.  It’s just that healthcare isn’t set up that way.  Our entire world now, in every industry and facet of life, is about data, analytics, and metrics.  Other industries have learned that rapid feedback loops are effective.  Adjusting a PWD’s insulin to carbohydrate dosing ratio should be no different.  By the time he comes back to my office three months later, the opportunity for learning may already have been lost.  Neither one of us has gotten timely and relevant feedback about our decisions.  We may have lost the opportunity for a teachable moment.  Healthcare needs to develop a new model where these feedback loops are much tighter and much faster, actually capitalizing on opportunities for teachable moments.  (Sidebar: One doctor who realized this years ago was Dr. Jordan Shlain, who founded HealthLoop)  Research studies show that PWDs are more successful and confident with managing their diabetes when they feel like they have the backup and support of their clinical providers looking over their shoulders to make sure things are going ok.  If we were to design the system from scratch to accomplish these goals, we probably would not have built it to rest on the concept of office visits every three months.

So, what should be the future model of a Diabetes and Endocrinology clinical practice?  Here’s what I imagine my practice looking like in the (hopefully near) future.  Instead of having 16 office visit slots per day of 30 minutes each, I imagine myself seeing 5 patients a day for 45-60 minutes each, allowing us to take our time working together in person and truly addressing the needs and goals of the patient.  These longer visits are essential for a patient new to my practice, a patient with a complicated or unknown diagnosis, a patient with complications or a major change in their disease state, or for discussing major changes in therapeutic course or strategy.  The rest of my day will be spent using a dashboard to do remote population management, looking for trouble spots among my patient population and focusing in on those, and doing telemedicine, connecting with patients through video-chats to make more minor adjustments and to do brief “check ins.”  Ten minutes spent with a patient at the point where there is a teachable moment like a low blood sugar from walking the dog might be more effective than a standard 30 minute office visit every three months.  We’ll have to test this hypothesis, of course, but we must try it.

This is why I’m brimming with so much enthusiasm and excitement about working with the non-profit, Tidepool, who is building an open data platform and a new generation of software applications for the management of type 1 diabetes.  Tidepool will provide us with the technology infrastructure to reach this vision of more frequent feedback loops and teachable moments.  I’m also very excited about the work that my UCSF colleagues, Drs. Ralph Gonzales and Nat Gleason, are doing to pilot the use of telephone visits and e-visits with patients in place of office visits.  Their work is paving the way toward demonstrating efficacy of e-visits, helping to achieve payer reimbursement so that such a model can take root.

The Future of Diabetes Management: Social Networking and New Technologies

I gave a talk yesterday to a great crowd at the annual UCSF CME conference, Diabetes Update.  The slides from my presentation, “The Future of Diabetes Management: Social Networking and New Technologies,” can be viewed on Slideshare.

The Surgeon’s Viewpoint: Swedish Obese Subjects Study and Bariatric Surgery

The Swedish Obese Subjects study is a fabulous example of how very-useful practical knowledge can come out of a well-conducted cohort study.  Not everything has to be a prospective randomized controlled trial!   This study has produced a number of landmark papers which provide convincing evidence that:

1.       Bariatric surgery offers survival benefit over the long term for the morbidly obese, despite the up-front mortality risk from the surgery itself.

2.       Bariatric surgery reduces cardiovascular and cancer deaths

3.       Bariatric surgery is durable: most patients do not regain the weight back

4.       Not all bariatric procedures are the same.  Some work better than others.

5.       Diets, behavioral modification, and “professional” weight loss coaching doesn’t really work for the morbidly obese in the long haul.

6.       And now….bariatric surgery prevents onset of diabetes!

The strength of the Swedish Obese Subjects trial is in the follow-up.  Since Sweden has a nationalized health care system, follow-up was completed on >95% of the initial cohort.  Such a trial could never be conducted in the United States….our people change jobs, towns, or insurances just way too often!

And there is just one more thing you should know about the Swedish Obese Subjects trial: the vast majority of the surgery cohort underwent vertical banded gastroplasty (VBG).  What’s that, you ask?  It was a first-generation bariatric operation that has been abandoned worldwide in favor of better (i.e. more effective) operations, such as gastric bypass and sleeve gastrectomy.  So if this trial were repeated in 2012, we would expect even better results in the surgical arm with fewer complications.

So where does that leave us?  For any patient with BMI > 40 (or BMI >35 with metabolic disease), you should really get them thinking about surgery as an option.  It’s not just about weight, and certainly has nothing to do with cosmetic appearance.  It’s about getting serious about treating metabolic disease: diabetes, hypertension, sleep apnea, hypercholesterolemia, PCOS, and others.  It’s about making sure that those diseases never develop in the first place.  It’s about reducing overall cancer risk, stroke risk, and heart attack risk.  And it’s about improving overall quality and quantity of life.

So why, then, with such powerful clinical evidence, do less than 1% of adults who would benefit from bariatric surgery actually get it?  That, my friend, is complicated, and probably worth another blog in its own right!

Jonathan Carter, MD


Can bariatric surgery prevent diabetes?

I’ve previously written here about the 2 major New England Journal trials looking at treating type 2 diabetes with bariatric surgery.  Those studies showed a very robust ability of bariatric surgery to treat type 2 diabetes.  If you can use bariatric surgery to treat type 2 diabetes, what about prevention?  This question was examined in a more recent NEJM publication of selected results from the Swedish Obese Subjects (SoS) study from Carlsson et al.

Guest Post by Dr. Jonathan Carter

I’m pleased to say that my friend and colleague, Dr. Jonathan Carter, has agreed to follow this post with a guest blog post of his own, giving his analysis of the study.  Dr. Carter is an Assistant Professor of Surgery at UCSF, frequently performing bariatric surgery.

For those who skim blogs…

I’ll start with my take-away points, and then go backwards to analyze the study in more depth.  So, without further ado, the major takeaways from this study are:

1) Bariatric surgery impressively reduced the risk of type 2 diabetes in a middle-aged, obese population by 80% compared to the control group.  The number needed to treat (NNT) was 1.3!

2) This study did not address the most important comparison, i.e. between bariatric surgery and an intensive lifestyle modification program.  Unfortunately, the control group in this study received minimal attempt at lifestyle modification.  Prior studies like the Diabetes Prevention Program, the Finnish Diabetes Prevention Study, and the Chinese Diabetes Prevention Study showed between a 30-50% reduction in type 2 diabetes incidence with lifestyle modification.  However, one cannot directly compare the rates in these studies to each other.

3) Due to #s 1 and 2 above, the next study should directly compare bariatric surgery and intensive lifestyle modification with regard to diabetes prevention.

4) Weight loss prevents the onset of type 2 diabetes in obese patients.  Bariatric surgery causes weight loss.

With these results, we have to start discussing whether it is ethical, reasonable, and cost-effective to use bariatric surgery to prevent type 2 diabetes.

Now, for those of you interested in some more information about the study and results, keep reading…


This study was a prospective, non-randomized trial which enrolled 4,047 obese patients from 1987-2001 in Sweden.  The researchers note that they did not randomize the participants due to “ethical reasons related to the high postoperative mortality associated with bariatric surgery in the 1980s.”  In other words, enough people died from bariatric surgery at the time the study began that it would have been unethical for them to randomly assign people to have it done.

The control group was selected by a matching algorithm that concurrently tried to keep the current mean values of the matching variables between the two groups as similar as possible.  Included patients were aged 37-60 years old and had BMI over 34 for men and over 38 for women.  And, of course, they did not have diabetes at baseline.  Ultimately, those included in this analysis were 1,658 patients who had surgery and 1,771 who were in the control group.

Baseline characteristics: Surgery group had more severe risk factors

Due to the matching process, those in the surgery group were older, heavier (120 kg vs 114 kg), had higher insulin levels, higher blood pressures, worse cholesterol, higher smoking rates, lower physical activity rates, and higher caloric intakes compared to those in the control group.  Because the groups were non-randomized, it was likely that these “sicker” and “riskier” patients were more likely to be recommended surgery by their physicians.  However, in the end, this makes the results even more impressive because the surgical group had 80% lower rates of diabetes despite being a sicker group to begin with.  The surgical group had the decks stacked against them, and still came out ahead.  It is as if the surgical group started a 100 meter race with a 1-2 second handicap, but was still able to win.

No attempt at standardizing lifestyle therapy in control group

As I discussed above, a weakness of this study is that there was no attempt to standardize treatments in the control group.  Some might say that this is a positive because it reflects “real-world” treatments.  And indeed, the authors note that “patients in the control group received the customary treatment for obesity at their primary health care centers.”  However, according to questionnaires, this meant that only 54% of these patients received even some professional guidance.  So, nearly half of the control group received no help at all from their healthcare providers with weight loss.

The Results: Surgery caused weight loss and prevented diabetes

These two figures say it all… compared to “customary treatment” in this cohort of obese patients, the patients who got bariatric surgery lost significantly more weight (Figure S3) and had significantly less progression to type 2 diabetes (Figure 1A).

New Dexcom CGM is FDA Approved

The next generation “G4” Dexcom CGM is now FDA approved and available in the US.  Press release is here.


Do insulin pumps and continuous glucose monitors actually improve outcomes?

Nearly every day in my practice, a patient with diabetes asks me whether he or she should switch from multiple daily insulin injections to an insulin pump.  I often have a discussion with patients about whether or not they should be using a CGM (continuous glucose monitor) to help monitor blood glucose instead of just using SMBG (self-monitoring of blood glucose).  As an endocrinologist, it is very important to be able to advise patients about specifically what these new technologies have to offer them.  Do they decrease mortality?  Do they decrease long-term diabetes complications?  Do they improve glycemic control?  Do they improve quality of life for patients?  Do they lower costs?  All new medical technologies need to undergo a rigorous evaluation and testing with these types of questions in mind.  This is critical not just so that I can be honest and helpful to my patients, but also from the overall perspective of the healthcare system.

In that vein, Yeh et al recently published a meta-analysis in the Annals of Internal Medicine called “Comparative Effectiveness and Safety of Methods of Insulin Delivery and Glucose Monitoring for Diabetes Mellitus: A Systematic Review and Meta-analysis.”

This meta-analysis, funded by AHRQ, looked at the differences between:

  1. MDI vs CSII (multiple daily injections vs continuous subcutaneous insulin infusion)
  2. Type 1 vs type 2 diabetes
  3. SMBG (self-monitoring of blood glucose) vs rt-CGM (real-time continuous glucose monitoring)

What types of studies did they include in their meta-analysis?

  • Studies of adults, adolescents, or children with type 1 or type 2 diabetes mellitus
  • Studies from 1966-2012
  • 19 studies comparing CSII with MDI (>3 injections per day of either basal/bolus insulin or NPH/regular)
  • 10 studies comparing CGM with SMBG (>3 fingersticks per day)
  • 4 studies comparing SAP (Sensor-augmented pump) use with MDI + SMBG

* Studies were excluded if regular insulin was used in the CSII (pump) group (they felt this to be a weakness of prior analyses)

Here is the key data table:

A few things pop out from this table:

  1. Overall, they assessed the strength of evidence as relatively weak.
  2. In children and adolescents, CSII showed no difference in clinical outcomes from MDI.  CSII was better in terms of quality-of-life.
  3. In adults with type 1 diabetes, CSII led to more symptomatic hypoglycemia, but better hemoglobin A1c and quality-of-life.
  4. There were no differences between CSII and MDI in adults with type 2 diabetes.
  5. CGM, whether with an insulin pump or not, led to a benefit in glycemic control without any difference in hypoglycemia.

Some concerns and words of caution when interpreting these results:

  • Meta analyses can always suffer from publication bias.  That is, studies are much more likely to be published if they show positive results.  So it is possible that studies have been done that generated results that would have shown no difference between the two methods being studied, but these may never have been published and thus cannot be included in the meta-analysis.
  • These studies all had durations of 12-52 weeks.  There were no studies reporting on long-term outcomes like micro or macrovascular disease.
  • 24 of the articles (approximately 2/3) were supported by pharmaceutical companies

What does this mean?

According to this meta-analysis, CGMs did improve glycemic control.  Insulin pumps did not appear to have a significant effect on clinical outcomes, but did positively effect quality of life.  Remember that the studies included were all between 12 and 52 weeks, so one major limitation is that any longer-term effects would not be teased out.

While some may discount the quality of life improvements seen with the pump as being less important than clinical outcomes, I caution people from doing so.  In a condition as omnipresent as diabetes, maintaining good quality of life for the patient is critical and a very important goal.

In the end, the decision about whether or not to use one of these devices comes down to a conversation with the patient and their family, based on their personal preferences and what each device might offer them in terms of benefits and harms.  This meta-analysis adds some more information to that conversation.

Finally, this meta-analysis shows that we simply need more data to study so that more concrete conclusions can be drawn.

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